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High-powered electric vehicle (EV) charging can significantly increase charging costs due to peak-demand charges. This paper proposes a novel charging algorithm which exploits typically long plugin sessions for domestic chargers and reduces…
Electronic structure is ubiquitously obtained via density functional theory (DFT), where the charge density plays a central role. This work presents EdenGNN (Equivariant Density Graph Neural Network), a machine learning (ML) charge density…
Charge transport is a revealing probe of the quantum properties of materials. Strong interactions can blur charge carriers resulting in a poorly understood "quantum soup". Here we study the conductivity of the Fermi-Hubbard model, a testing…
We find that at intermediate temperatures, the metallic temperature dependence of the conductivity \sigma(T) of 2D electrons in silicon is described well by a recent interaction-based theory of Zala et al. (Phys. Rev. B 64, 214204 (2001)).…
Accurate estimation of battery state of health is crucial for effective electric vehicle battery management. Here, we propose five health indicators that can be extracted online from real-world electric vehicle operation and develop a…
The results obtained in Mainz in 1982 year were check up. The analysis of data from this work was made at momentum transfer range $q = 0.25 \div 0.75 fm^{-1}$ using the model independent form factor (the expansion of form factor in a power…
The active element pattern method is widely employed in beam pattern synthesis of array antenna to account for mutual coupling between antenna elements. Calculating the active element patterns for large number of array requires full-wave…
The precision data on Z boson decays from LEP-I and SLC colliders are compared with the predictions based on the Minimal Standard Theory. The Born approximation of the theory is based on three most accurately known observables: G_mu -- the…
Role of the Coulomb interaction, mean fissility, mass asymmetry, and charge asymmetry parameters on the synthesis of heavy and superheavy elements has been examined with respect to the deformation parameters of the projectile and target…
The properties of electrons in matter are of fundamental importance. They give rise to virtually all molecular and material properties and determine the physics at play in objects ranging from semiconductor devices to the interior of giant…
Machine learning (ML) techniques have rapidly found applications in many domains of materials chemistry and physics where large data sets are available. Aiming to accelerate the discovery of materials for battery applications, in this work,…
At the future high luminosity electron-positron collider FCC-ee proposed for CERN, the precise measurement of the charge asymmetry in $e^+ e^- \to \mu^+ \mu^-$ near the Z resonance is of special interest. In particular, such a measurement…
We perform a determination of the strong coupling constant using the latest ATLAS inclusive jet cross section data, from proton-proton collisions at sqrt{s}=7 TeV, and their full information on the bin-to-bin correlations. Several…
The Lorenz ratio serves as a measure to compare thermal and electric conductivities of metals. Recent experiments observed small Lorenz ratios in the compensated metal WP$_2$, indicating that charge flow is strongly favored over heat…
Bound electron pairs formed due to the peculiarities of the band dispersion of electrons in crystals attract much interest because they can carry charge and spin even in the absence of band conductivity. However, such an important parameter…
Multi-task learning (MTL) in materials science relies on the assumption that physically related properties share learnable representations. We challenge this assumption using a 54,028-sample metal alloy dataset exhibiting extreme task-level…
We show that electron-ion structure factors in fluid metallic systems can be well understood from an application of linear response in the electron system, combined with hard-sphere like correlation for the ionic component. In particular,…
With the rapid development of artificial intelligence, the combination of material database and machine learning has driven the progress of material informatics. Because aluminum alloy is widely used in many fields, so it is significant to…
In this thesis a new model for calculating the total energy of atomic and solid systems is presented. The model is used to study the properties of the Si(100) surface and dislocation dynamics in the diamond structure. For the Si(100)…
In this paper we analyze the behavior of hydrophobic polyelectrolytes. It has been proposed that this system adopts a pearl-necklace structure reminiscent of the Rayleigh instability of a charged droplet. Using a Poisson-Boltzmann approach,…